Triple

T25599282
Position Surface form Disambiguated ID Type / Status
Subject Central Mineral Baths of Sofia E641740 entity
Predicate locatedNear P294 FINISHED
Object Sofia Largo
Sofia Largo is a prominent architectural and historical complex in central Sofia, Bulgaria, known for its monumental socialist-era government buildings and expansive public square.
E1686780 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sofia Largo | Statement: [Central Mineral Baths of Sofia, locatedNear, Sofia Largo]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sofia Largo
Triple: [Central Mineral Baths of Sofia, locatedNear, Sofia Largo]
Generated description
Sofia Largo is a prominent architectural and historical complex in central Sofia, Bulgaria, known for its monumental socialist-era government buildings and expansive public square.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e75dc60d108190b7e2419e36b0134b completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f9a53aa48190b935de0228cb5be3 completed May 2, 2026, 1:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10b7708fc08190bee8f889b590077a completed May 22, 2026, 8:07 p.m.
NEDg Description generation batch_6a10b84ad3ac8190b78bec4cd68a84e8 completed May 22, 2026, 8:10 p.m.
NED2 Entity disambiguation (via description) batch_6a10b96903108190bd27481597bf46fa completed May 22, 2026, 8:15 p.m.
Created at: April 21, 2026, 4:30 p.m.